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Risk of Extreme Events in Multiobjective Decision Trees Part 2. Rare Events

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  • Hendrik I. Frohwein
  • Yacov Y. Haimes
  • James H. Lambert

Abstract

Earlier work with decision trees identified nonseparability as an obstacle to minimizing the conditional expected value, a measure of the risk of extreme events, by the well‐known method of averaging out and folding back. This second of two companion papers addresses the conditional expected value that is defined as the expected outcome assuming that a random variable is observed only in the upper 100 (1 −α) percent of potential outcomes, where α is a cumulative probability preselected by the decision maker. An approach is proposed to overcome the need to evaluate all policies in order to identify the optimal policy. The approach is based in part on approximating the conditional expected value by using statistics of extremes. An existing convenient approximation of the conditional expected value is shown to be separable into two constituent elements of risk and can thus be optimized, along with other objectives including the unconditional expected value of the outcome, in a multiobjective decision tree. An example of sequential decision making for remediation or environmental contamination is provided. The importance of the results for risk analyis beyond the minimization of conditional expected values is pointed out.

Suggested Citation

  • Hendrik I. Frohwein & Yacov Y. Haimes & James H. Lambert, 2000. "Risk of Extreme Events in Multiobjective Decision Trees Part 2. Rare Events," Risk Analysis, John Wiley & Sons, vol. 20(1), pages 125-134, February.
  • Handle: RePEc:wly:riskan:v:20:y:2000:i:1:p:125-134
    DOI: 10.1111/0272-4332.00012
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    Citations

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    Cited by:

    1. Nilesh N. Joshi & James H. Lambert, 2011. "Diversification of infrastructure projects for emergent and unknown non-systematic risks," Journal of Risk Research, Taylor & Francis Journals, vol. 14(6), pages 717-733, June.
    2. Barry M. Horowitz & Yacov Y. Haimes, 2003. "Risk‐based methodology for scenario tracking, intelligence gathering, and analysis for countering terrorism," Systems Engineering, John Wiley & Sons, vol. 6(3), pages 152-169.
    3. Kash Barker & Kaycee J. Wilson, 2012. "Decision Trees with Single and Multiple Interval-Valued Objectives," Decision Analysis, INFORMS, vol. 9(4), pages 348-358, December.
    4. Barker, Kash & Haimes, Yacov Y., 2009. "Assessing uncertainty in extreme events: Applications to risk-based decision making in interdependent infrastructure sectors," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 819-829.
    5. Frini, Anissa & Guitouni, Adel & Martel, Jean-Marc, 2012. "A general decomposition approach for multi-criteria decision trees," European Journal of Operational Research, Elsevier, vol. 220(2), pages 452-460.
    6. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    7. Ruth Y. Dicdican & Yacov Y. Haimes, 2005. "Relating multiobjective decision trees to the multiobjective risk impact analysis method," Systems Engineering, John Wiley & Sons, vol. 8(2), pages 95-108.

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